The present invention relates generally to analysis of emboli, and more particularly to automatically analyzing the affected region due to an embolism in an organ.
Embolism is the obstruction of a blood vessel by a foreign substance. Blood clots are the most common cause of embolism. A pulmonary embolus is a blood clot that has been carried through the blood stream into a pulmonary artery (blood vessels proceeding from the heart into the lungs) partially or fully blocking that vessel. The term “embolus” refers to the plug obstructing the blood vessel while embolism refers to the process by which this happens.
Although Pulmonary Embolism (PE) is a common causes of unexpected death, it may often be preventable. Prompt treatment with anti-coagulants is essential to prevent loss of life. However, treatments also carry risks, so correct diagnosis is critical. Computed tomography angiography (CTA) is gaining increasing acceptance as a method of diagnosis, offering sensitivity and specificity comparable or superior to alternative methods such as pulmonary angiography and ventilation-perfusion scans. CTA is rapid and non-invasive, and in many cases has the benefit of allowing an alternative diagnosis to explain a patient's symptoms.
Images acquired from 16-slice Computed Tomography (CT) machines of contrast-injected patients provide very high-resolution data, allowing for better detection of emboli located in sub-segmental arteries. This high resolution three dimensional data offers the potential for precise analysis of the effects of PEs on the lungs, but such assessments may be infeasible without automation.
Current techniques for automated analysis of PE within contrast-enhanced CT images relate to the direct detection of the clots themselves within the arteries, or indirect inference of clot location by visualization of perfusion defects in affected lung area(s). In the former case, a good segmentation of the arteries is generally required in order to detect the precise locations of PEs. Detection of clots can then be done through a visualization technique or through Computer Aided Detection (CAD).
In another technique for automated analysis of CTA, the mean density of local areas of the lungs are computed and rendered to directly visualize perfusion defects. Lung areas showing lower than average density may be suggestive of an upstream clot. An advantage of this technique is that it gives a graphical representation of the extent and severity of the disease. However a disadvantage is that in order to properly measure perfusion, two scans are required, before and after contrast, requiring a complicated acquisition and twice as much radiation. In addition, non-rigid registration is required to align the two scans, which is difficult and time-consuming. Currently the accepted clinical practice for evaluating patients with possible PE is to perform only a single post-contrast scan.
Therefore, what is needed is an automated technique for analyzing from a single scan the extent to which embolism affects an organ.